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Qwen3.8-Flash

Qwen · OpenAI-compatible API

qwen/qwen3.8-flash

USD / 1M tokens

Input$0.13
Cached Input$0.02
Output$0.42
Context
1M
Tool Calling
✓
Reasoning
✓
Vision
✓
Streaming
✓
OpenAI-compatible API
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.iteracompute.com/v1",
    api_key=os.environ["ITERACOMPUTE_API_KEY"],
)
response = client.chat.completions.create(
    model="qwen/qwen3.8-flash",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Catalog snapshot: 2026-10-16. Live prices have not been verified yet.

Overview

Qwen3.8-Flash is available through the IteraCompute OpenAI-compatible API, with 1M context, streaming and reasoning.

Tasks and selection tradeoffs

Short text extraction

Extract named fields from a supplied document and validate the schema.

Coding assistant trials

Try one small code change with a failing test and review the result.

Task suggestions based on catalog features and price, not model quality benchmarks.

Choose your tool

Choose a model and tool for your task →

Model capabilities

Features available through this model interface. Updated October 16, 2026.

CapabilityModel developer documentationRoute test
Tool callingSupportedSupported
ReasoningSupportedSupported
Image inputSupportedSupported
StreamingSupportedSupported
JSON mode (json_object)SupportedSupported

Context: 1M · Output limit: 128K

Model developer documentation

Set thinking controls per model. Use one control style per request.

For JSON responses, validate your application schema before use. Input and requested output share the context budget.

Pricing

Prices in USD per 1M tokens.

Input$0.13
Cached Input$0.02
Output$0.42

Example task: Extract fields from a document

Assume 12,000 aggregate input tokens and 1,000 billable output tokens across all calls. No cache hit.

12,000 × $0.13 / 1M + 1,000 × $0.42 / 1M = $0.001980

If usage actually reports 9,000 of those input tokens as cached, replace that portion at the cached-input rate ($0.02/1M): $0.000990. Cached tokens are part of total input, never added on top.

Illustrative calculation using the 2026-10-16 catalog snapshot. Include every agent call and retry, repeated history and billable reasoning output; settle against actual usage and current Console prices.

Usage limits

  • Input and requested maximum output share the context budget. Keep both within the model limits.
  • Split long workflows into bounded steps and handle tool errors and retries in your application.
  • Reasoning tokens are billable output. Reserve enough generation budget to obtain a final text reply.
  • View current availability and prices in the Console.

API parameters

Parameter / protocol fieldUsage
model / messagesUse the exact model ID and chat message list
stream=true / stream_options.include_usage=trueReceive SSE chunks, [DONE] and final usage
tools / tool_calls / role=toolDefine functions in tools, execute tool_calls and return results with role=tool
response_format.type=json_objectRequest valid JSON; validate the required structure in your application
reasoning_contentReasoning output is separate from the final reply and counts toward output usage
{"enable_thinking":false}Supported; use one thinking-control style per request
{"enable_thinking":true}Supported; use one thinking-control style per request

API

Base URL
https://api.iteracompute.com/v1
Endpoint
POST /v1/chat/completions
Model ID
qwen/qwen3.8-flash
Authentication
Authorization: Bearer ITERACOMPUTE_API_KEY

View Docs

FAQ

How do I use Qwen3.8-Flash with the OpenAI SDK?

Set base_url to https://api.iteracompute.com/v1 and model to qwen/qwen3.8-flash. Authenticate with your IteraCompute API key.

What does Qwen3.8-Flash cost?

See the pricing section for current input, cached-input and output rates in USD per 1M tokens. Check the refresh time before use.

What context length is available?

1M. Input and requested maximum output share the context budget.

Ready for your first request?

Create your key, choose a tool and get a non-empty first reply.